Modeling and Simulation in computer science

Chapters

1Foundations of Modeling in Computer Science

2Mathematical Foundations for Simulation

3Discrete-Event Simulation Fundamentals

4Agent-Based Modeling and Complex Systems

5System Dynamics and Continuous Modeling

6Numerical Methods and Scientific Computing for Simulation

7Stochastic Processes and Uncertainty Quantification

8Data Structures, Algorithms, and Simulation Efficiency

9Simulation Programming Languages and Frameworks

10Verification, Validation, and Experiment Design

11Performance Analysis and Optimization of Simulations

12High-Performance Computing and Parallel Simulation

13Data Management, Reproducibility, and Experiment Tracking

Data Provenance and Lineage Data Cleaning for Simulations Metadata Standards for Models Experiment Tracking Tools Reproducible Environments and Containers Version Control for Data and Models Data Storage Architectures Secure Data Sharing and Access Control Benchmark Datasets for Simulation Data Visualization for Records Provenance in Collaborative Projects Documentation and Recording of Experiments Numerical Precision Management Ethical Data Usage and Privacy Long-Term Data Preservation

14Visualization and Communication of Simulation Results

15Applications and Case Studies in Modeling and Simulation

Courses/Modeling and Simulation in computer science/Data Management, Reproducibility, and Experiment Tracking

Data Management, Reproducibility, and Experiment Tracking

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Establish robust data handling, versioning, and reproducible research practices for simulations.

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Data Provenance and Lineage

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